Llama 2 70B Chat on Apple M2 Pro (32 GB)

Can the Apple M2 Pro (32 GB) run Llama 2 70B Chat?

3 pts

No, it doesn’t fit

No. Llama 2 70B Chat needs about 31.2 GB even at Q2_K; the Apple M2 Pro (32 GB) has 21.4 GB usable.

Download Llama 2 70B Chat

Recommended: Q2_K. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run llama2:70b-chat-q2_K

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q2_K file (opens in a new tab)

huggingface.co/TheBloke/Llama-2-70B-Chat-GGUF (opens in a new tab)

ollama run hf.co/TheBloke/Llama-2-70B-Chat-GGUF:Q2_K

Original weights · Hugging Face

Full-precision files from Meta, for fine-tuning, vLLM, Transformers.

huggingface.co/meta-llama/Llama-2-70b-chat-hf (opens in a new tab)

Free Hugging Face account needed: request access on the model page, and Meta approves it (usually within minutes to a few hours).

Official repo · GitHub

Reference code, inference scripts and docs from Meta. The weights themselves download from Hugging Face.

github.com/meta-llama/llama (opens in a new tab)

git clone https://github.com/meta-llama/llama

Meta’s original Llama 2 repo (now archived).

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the F grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	3.4 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Total	3.4 / 100	3 ptsWon't run (F) · 3 of 100 points: Model quality 3.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the Apple M2 Pro (32 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	31.2 GB	21.4 GB	—	Won't run	3 ptsWon't run (F) · 3 of 100 points: Model quality 3.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q3_K_M`	37.5 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q4_K_M`	45.7 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q5_K_M`	52.6 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q6_K`	60.2 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
`Q8_0`	76.8 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
`F16`	142 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	Original weights (opens in a new tab)

Memory figures assume 4K of context. Longer conversations or documents grow the KV cache.

Hardware that can run it

65 ptsGood (B) · 65 of 100 points: Model quality 15.4/45, Memory fit 25.0/25, Speed 13.4/15, Memory use 11.7/15 NVIDIA RTX PRO 6000 Blackwell Q4_K_M · 31.9 tok/s
65 ptsGood (B) · 65 of 100 points: Model quality 11.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q2_K · 52.4 tok/s
61 ptsGood (B) · 61 of 100 points: Model quality 13.6/45, Memory fit 25.0/25, Speed 7.8/15, Memory use 15.0/15 Apple M4 Max (64 GB) Q3_K_M · 10.8 tok/s
60 ptsGood (B) · 60 of 100 points: Model quality 13.6/45, Memory fit 25.0/25, Speed 6.7/15, Memory use 15.0/15 Apple M1 Max (64 GB) Q3_K_M · 7.9 tok/s
59 ptsGood (B) · 59 of 100 points: Model quality 15.4/45, Memory fit 25.0/25, Speed 6.9/15, Memory use 12.4/15 Apple M4 Max (128 GB) Q4_K_M · 8.4 tok/s
57 ptsUsable (C) · 57 of 100 points: Model quality 15.4/45, Memory fit 25.0/25, Speed 8.3/15, Memory use 8.9/15 Apple M2 Ultra (192 GB) Q4_K_M · 12.3 tok/s

Models that do run on the Apple M2 Pro (32 GB)

91 ptsExcellent (S) · 91 of 100 points: Model quality 39.5/45, Memory fit 24.0/25, Speed 12.5/15, Memory use 15.0/15 Gemma 4 26B-A4B Q4_K_M · 27.8 tok/s
89 ptsExcellent (S) · 89 of 100 points: Model quality 35.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Qwen3.6 35B-A3B Q3_K_M · 45.6 tok/s
89 ptsExcellent (S) · 89 of 100 points: Model quality 35.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Qwen3.5 35B-A3B Q3_K_M · 45.6 tok/s
88 ptsExcellent (S) · 88 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GLM-4.7 Flash (30B-A3B) Q3_K_M · 45.6 tok/s
88 ptsExcellent (S) · 88 of 100 points: Model quality 34.0/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Ornith 1.5 35B-A3B Q3_K_M · 45.6 tok/s

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.